ICE: a statistical approach to identifying endmembers in hyperspectral images

Author

Berman, Mark ; Kiiveri, Harri ; Lagerstrom, Ryan ; Ernst, Andreas ; Dunne, Rob ; Huntington, Jonathan F.

Author_Institution

Macquarie Univ. Campus, North Ryde, NSW, Australia

Volume

42

Issue

10

fYear

2004

Firstpage

2085

Lastpage

2095

Abstract

Several of the more important endmember-finding algorithms for hyperspectral data are discussed and some of their shortcomings highlighted. A new algorithm - iterated constrained endmembers (ICE) - which attempts to address these shortcomings is introduced. An example of its use is given. There is also a discussion of the advantages and disadvantages of normalizing spectra before the application of ICE or other endmember-finding algorithms.

Keywords

data acquisition; geophysical signal processing; geophysical techniques; image processing; minerals; remote sensing; spectral analysis; statistical analysis; ICE; convex geometry; endmember identification; endmember-finding algorithms; hyperspectral data; hyperspectral images; iterated constrained endmembers; spectra normalization; statistical approach; Australia; Brightness; Hyperspectral imaging; Ice; Layout; Minerals; Noise shaping; Packaging; Solid modeling; Spectral shape; Convex geometry; endmember; hyperspectral; normalization; simplex;

fLanguage

English

Journal_Title

Geoscience and Remote Sensing, IEEE Transactions on

Publisher

ieee

ISSN

0196-2892

Type

jour

DOI

10.1109/TGRS.2004.835299

Filename

1344161